Rolling bearings are the main components of rotating machines which are mostly damaged. Therefore, correct and quick fault diagnosis of rolling bearings is very necessary for maintenance. Nowadays, machine learning has emerged as a very effective artificial intelligence technique for fault diagnosis. The Naive Bayes classifier is one of the machine learning techniques that effectively classifies faults. In this work, intelligent fault classification of bearing faults based on Naive Bayes is proposed. The proposed model correctly classifies the different types of fault conditions of rolling bearings. The proposed model has achieved the best results and has been compared with existing methods.